1. A data engineer is using AWS Batch to run a job that requires a Docker image to be built and then run on a set of compute resources. The Docker image has several dependencies that must be installed before the job can run. Which of the following options should the data engineer choose to ensure that the Docker image is built with the necessary dependencies and runs correctly on the compute resources?

A) Use an AWS CodePipeline to build the Docker image and upload it to an Amazon ECR repository. Configure the job definition in AWS Batch to use the Docker image from the ECR repository.
B) Create a custom AMI with the necessary dependencies and use it to launch an EC2 instance. Configure the job definition in AWS Batch to use the EC2 instance as the compute environment.
C) Use an AWS Lambda function to build the Docker image and upload it to an Amazon ECR repository. Configure the job definition in AWS Batch to use the Docker image from the ECR repository.
D) Create a custom Dockerfile that installs the necessary dependencies and builds the Docker image. Upload the Dockerfile to an Amazon S3 bucket, and configure the job definition in AWS Batch to use the Dockerfile to build the Docker image.



2. You need to deploy a high-performance file system that can be shared across multiple compute instances in your Amazon Web Services (AWS) environment. You want to use Amazon FSx for this purpose. Which of the following statements is true regarding Amazon FSx?

A) Amazon FSx uses Amazon S3 as its underlying storage backend.
B) Amazon FSx does not support data compression.
C) Amazon FSx for Windows File Server is suitable for Linux workloads.
D) Amazon FSx can only be accessed by a single compute instance at a time.
E) Amazon FSx for Lustre is ideal for data-intensive workloads, such as machine learning, high-performance computing, and video processing.


3. You have a large dataset of customer transactions that you want to analyze using Amazon Kinesis Data Analytics. You want to perform a series of SQL-based transformations on the data, including filtering, aggregating, and joining multiple streams. Which of the following is a recommended best practice for designing your Kinesis Data Analytics application?

A) Use multiple SQL statements to perform each transformation in a separate pass
B) Use AWS Glue to pre-process the data before ingesting it into Kinesis Data Analytics
C) Use a single SQL statement to perform filtering and aggregation, and a separate SQL statement to perform join operations
D) Use a single SQL statement to perform all transformations in one pass



4. You are building a natural language processing application that requires real-time inference with high accuracy. You want to deploy your machine learning model on AWS, but you're not sure which service to choose. Which of the following AWS services would be the best fit for this use case?

A) Amazon Comprehend
B) Amazon SageMaker Neo
C) Amazon SageMaker Batch Transform
D) Amazon Elastic Inference



5. Which of the following statements is true regarding network ACLs and security groups in Amazon VPC, and which one is a key difference between the two?

A) Network ACLs provide stateless filtering of traffic in and out of subnets in an Amazon VPC, while security groups provide stateful filtering of traffic to Amazon EC2 instances. A key difference between the two is that network ACLs can be associated with multiple subnets, while security groups can be associated with only one Amazon EC2 instance.
B) Network ACLs provide stateful filtering of traffic in and out of subnets in an Amazon VPC, while security groups provide stateless filtering of traffic to Amazon EC2 instances. A key difference between the two is that network ACLs can be associated with only one subnet, while security groups can be associated with multiple Amazon EC2 instances.
C) Network ACLs provide stateful filtering of traffic in and out of subnets in an Amazon VPC, while security groups provide stateless filtering of traffic to Amazon EC2 instances. A key difference between the two is that network ACLs can be associated with multiple subnets, while security groups can be associated with only one Amazon EC2 instance.
D) Network ACLs provide stateless filtering of traffic in and out of subnets in an Amazon VPC, while security groups provide stateful filtering of traffic to Amazon EC2 instances. A key difference between the two is that network ACLs can be associated with only one subnet, while security groups can be associated with multiple Amazon EC2 instances.